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Identifier 000410284
Title AmITest : a framework for semi - automated testing of Ambient Intelligence environments
Alternative Title AmITest : μία υποδομή για τον ημι-αυτόματο έλεγχο περιβαλλόντων διάχυτης νοημοσύνης
Author Λουλουδάκης, Νικόλαος
Thesis advisor Στεφανίδης, Κωνσταντίνος
Reviewer Σαββίδης, Αντώνιος
Αντώνα, Μαργαρίτα
Abstract Ambient Intelligence (Ami) has gradually evolved from an emerging research paradigm to an everyday reality (e.g., Internet of Things) and, therefore, end-users -ranging from IT-experts to novice users - have a need to program or adapt the behavior of "Smart" Environments. Programming such highly-distributed, heterogeneous and complex systems is a challenging task, let alone validating their behavioral aspects. The latter is a rather difficult but crucial process, since such factors eventually determine their acceptance and perceived usability. The AmITest framework facilitates testing and validation of the functionality of each individual artifact and of the environment's behavior as a whole in a straightforward manner. As a core component of the AmI Solertis - a development and orchestration studio for AmI Environments developed in the HCI Laboratory of ICS-FORTH -AmITest utilizes the available meta-information regarding the installed artifacts and behavior definitions, in order to simplify the overall testing process. More specifically, a wizard-like process enables even less-experienced users to easily compose the desired tests, while the test execution orchestration is automatically handled by the proposed framework. AmITest heavily relies on the widely used JavaScript language and a number of reliable frameworks, including the Promises for asynchronous programming and Mocha and Chai for testing, aiming to achieve maximum efficiency, along with the provision of an effective validation mechanism in the most straightforward manner. To minimize its footprint and increase its usability, AmITest optionally offers a sandboxed environment in which testing can be executed without affecting the actual system and its artifacts. Specifically, it provides artifact impersonation capabilities (e.g., mock how a smart artifact reacts to stimuli) and local behavioral script execution. Finally, the internal reporting system of AmITest delivers the test execution outcome to the tester through a rich Graphical User Interface (GUI) in order to assess the effectiveness of the behavioral script and validate the desired assertions and invariants. That information is also fed back to the AmI Solertis system to be further examined for potential erroneous behaviors and to ensure the environment's stability via its inherent continuous validation and integration process.
Language English
Issue date 2017-07-21
Collection   Faculty/Department--Faculty of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
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